Meat — Residuals by country
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Meat — Residuals is currently reported for 182 countries. The highest value is 16 1000 t in Guatemala; the lowest is -495 1000 t in China.
The median across all reporting countries is 0 1000 t, and the mean is -7.55 1000 t.
Over the past decade 18 countries rose and 29 fell. The largest increase was in Belarus (up 100.0%), and the largest decrease in Pakistan (down 700.0%).
Meat — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Guatemala | 16 1000 t | 2023 | — | volatile |
| 2 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 2 | Angola | 0 1000 t | 2023 | — | flat |
| 2 | Albania | 0 1000 t | 2023 | — | volatile |
| 2 | Argentina | 0 1000 t | 2023 | — | volatile |
| 2 | Armenia | 0 1000 t | 2023 | — | flat |
| 2 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 2 | Austria | 0 1000 t | 2023 | — | volatile |
| 2 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 2 | Bahrain | 0 1000 t | 2023 | — | flat |
| 2 | Bahamas | 0 1000 t | 2023 | — | flat |
| 2 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 2 | Belarus | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Belize | 0 1000 t | 2023 | — | volatile |
| 2 | Brazil | 0 1000 t | 2023 | — | volatile |
| 2 | Barbados | 0 1000 t | 2023 | — | volatile |
| 2 | Bhutan | 0 1000 t | 2023 | — | flat |
| 2 | Botswana | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Chile | 0 1000 t | 2023 | — | volatile |
| 2 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 2 | Congo | 0 1000 t | 2023 | — | flat |
| 2 | Colombia | 0 1000 t | 2023 | — | flat |
| 2 | Comoros | 0 1000 t | 2023 | — | flat |
| 2 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 2 | Cuba | 0 1000 t | 2019 | — | flat |
| 2 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 2 | Djibouti | 0 1000 t | 2023 | — | flat |
| 2 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 2 | Algeria | 0 1000 t | 2023 | — | volatile |
| 2 | Ecuador | 0 1000 t | 2023 | — | flat |
| 2 | Egypt | 0 1000 t | 2023 | — | volatile |
| 2 | Estonia | 0 1000 t | 2023 | — | volatile |
| 2 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 2 | Finland | 0 1000 t | 2023 | — | flat |
| 2 | Fiji | 0 1000 t | 2023 | — | volatile |
| 2 | Gabon | 0 1000 t | 2023 | — | flat |
| 2 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Ghana | 0 1000 t | 2023 | — | flat |
| 2 | Guinea | 0 1000 t | 2023 | — | flat |
| 2 | Gambia | 0 1000 t | 2023 | — | flat |
| 2 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 2 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Grenada | 0 1000 t | 2023 | — | flat |
| 2 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Honduras | 0 1000 t | 2023 | — | flat |
| 2 | Croatia | 0 1000 t | 2023 | — | flat |
| 2 | Haiti | 0 1000 t | 2023 | — | flat |
| 2 | Iraq | 0 1000 t | 2023 | — | flat |
| 2 | Iceland | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 2 | Jordan | 0 1000 t | 2023 | — | volatile |
| 2 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 2 | Kenya | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Cambodia | 0 1000 t | 2023 | — | flat |
| 2 | Kiribati | 0 1000 t | 2023 | — | flat |
| 2 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 2 | Kuwait | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Liberia | 0 1000 t | 2023 | — | flat |
| 2 | Libya | 0 1000 t | 2023 | — | flat |
| 2 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 2 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 2 | Lesotho | 0 1000 t | 2023 | — | flat |
| 2 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 2 | Latvia | 0 1000 t | 2023 | — | volatile |
| 2 | Madagascar | 0 1000 t | 2023 | — | flat |
| 2 | Maldives | 0 1000 t | 2023 | — | volatile |
| 2 | Mexico | 0 1000 t | 2023 | — | flat |
| 2 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 2 | Malta | 0 1000 t | 2023 | — | flat |
| 2 | Montenegro | 0 1000 t | 2023 | — | flat |
| 2 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 2 | Mozambique | 0 1000 t | 2023 | — | flat |
| 2 | Mauritania | 0 1000 t | 2023 | — | flat |
| 2 | Mauritius | 0 1000 t | 2023 | — | flat |
| 2 | Malawi | 0 1000 t | 2023 | — | volatile |
| 2 | Namibia | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Niger | 0 1000 t | 2023 | — | flat |
| 2 | Nigeria | 0 1000 t | 2023 | — | flat |
| 2 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 2 | Nepal | 0 1000 t | 2023 | — | flat |
| 2 | Nauru | 0 1000 t | 2023 | — | flat |
| 2 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Peru | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 2 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 2 | Qatar | 0 1000 t | 2023 | — | flat |
| 2 | Rwanda | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Senegal | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 2 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 2 | El Salvador | 0 1000 t | 2023 | — | flat |
| 2 | Serbia | 0 1000 t | 2023 | — | volatile |
| 2 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 2 | Suriname | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 2 | Eswatini | 0 1000 t | 2023 | — | flat |
| 2 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 2 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 2 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 2 | Tonga | 0 1000 t | 2023 | — | flat |
| 2 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 2 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 2 | Uganda | 0 1000 t | 2023 | up 100.0% | volatile |
| 2 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 2 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 2 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 2 | Samoa | 0 1000 t | 2023 | — | flat |
| 2 | Yemen | 0 1000 t | 2023 | — | flat |
| 2 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Micronesia | 0 1000 t | 2023 | — | flat |
| 2 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 2 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 2 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 2 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 2 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 2 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 2 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 2 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 2 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 2 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 2 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 2 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 2 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 2 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 2 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 2 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 2 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 2 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 2 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 141 | Bangladesh | -1 1000 t | 2023 | — | volatile |
| 141 | Bulgaria | -1 1000 t | 2023 | unchanged | volatile |
| 141 | Germany | -1 1000 t | 2023 | — | volatile |
| 141 | Denmark | -1 1000 t | 2023 | down 100.7% | volatile |
| 141 | Lithuania | -1 1000 t | 2023 | — | volatile |
| 141 | Morocco | -1 1000 t | 2023 | — | volatile |
| 141 | North Macedonia | -1 1000 t | 2023 | — | volatile |
| 141 | Myanmar | -1 1000 t | 2023 | — | volatile |
| 141 | New Zealand | -1 1000 t | 2023 | — | volatile |
| 141 | Saudi Arabia | -1 1000 t | 2023 | unchanged | volatile |
| 141 | Zambia | -1 1000 t | 2023 | — | volatile |
| 141 | China, Hong Kong SAR | -1 1000 t | 2023 | — | volatile |
| 141 | Iran (Islamic Republic of) | -1 1000 t | 2023 | up 83.3% | volatile |
| 141 | Viet Nam | -1 1000 t | 2023 | — | volatile |
| 155 | India | -2 1000 t | 2023 | up 33.3% | volatile |
| 155 | Malaysia | -2 1000 t | 2023 | unchanged | volatile |
| 157 | Sweden | -3 1000 t | 2023 | — | volatile |
| 157 | Uruguay | -3 1000 t | 2023 | — | volatile |
| 159 | Hungary | -4 1000 t | 2023 | up 78.9% | volatile |
| 159 | Italy | -4 1000 t | 2023 | down 300.0% | volatile |
| 159 | Norway | -4 1000 t | 2023 | down 130.8% | volatile |
| 159 | Paraguay | -4 1000 t | 2023 | — | volatile |
| 163 | Australia | -5 1000 t | 2023 | down 145.5% | volatile |
| 163 | Indonesia | -5 1000 t | 2023 | up 28.6% | rising |
| 165 | Romania | -6 1000 t | 2023 | down 500.0% | volatile |
| 166 | Australia and New Zealand | -7 1000 t | 2023 | down 163.6% | volatile |
| 167 | Belgium | -8 1000 t | 2023 | — | volatile |
| 167 | Pakistan | -8 1000 t | 2023 | down 700.0% | volatile |
| 169 | Czechia | -10 1000 t | 2023 | — | volatile |
| 169 | Ukraine | -10 1000 t | 2023 | — | volatile |
| 171 | Slovenia | -14 1000 t | 2023 | — | volatile |
| 171 | Netherlands (Kingdom of the) | -14 1000 t | 2023 | — | volatile |
| 173 | France | -15 1000 t | 2023 | — | volatile |
| 174 | Russian Federation | -20 1000 t | 2023 | — | volatile |
| 175 | Spain | -23 1000 t | 2023 | up 72.0% | volatile |
| 176 | Ireland | -25 1000 t | 2023 | down 150.0% | volatile |
| 177 | United Arab Emirates | -31 1000 t | 2023 | down 342.9% | volatile |
| 178 | Türkiye | -34 1000 t | 2023 | down 88.9% | falling |
| 179 | Poland | -51 1000 t | 2023 | down 131.8% | volatile |
| 180 | Thailand | -75 1000 t | 2023 | down 74.4% | volatile |
| 181 | China, mainland | -494 1000 t | 2023 | down 24.7% | falling |
| 182 | China | -495 1000 t | 2023 | down 25.0% | falling |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Central America 16 1000 t
- Americas 5 1000 t
- South Africa 0 1000 t
- Central Asia 0 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 1000 t
- Small Island Developing States (SIDS) -1 1000 t
- Eastern Africa -1 1000 t
- Northern Africa -1 1000 t
- Western Africa -1 1000 t
- Low Income Food Deficit Countries (LIFDCs) -1 1000 t
- Northern America -3 1000 t
About this data
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per capita food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.